Lake water-level fluctuation forecasting using machine learning models: a systematic review
Lake water-level fluctuation is a complex and dynamic process, characterized by high
stochasticity and nonlinearity, and difficult to model and forecast. In recent years …
stochasticity and nonlinearity, and difficult to model and forecast. In recent years …
A review of models for water level forecasting based on machine learning
WJ Wee, NB Zaini, AN Ahmed, A El-Shafie - Earth Science Informatics, 2021 - Springer
It is crucial to keep an eye on the water levels in reservoirs in order for them to perform at
peak, as they are one of the, if not, the most vital part in water resource management. The …
peak, as they are one of the, if not, the most vital part in water resource management. The …
Transformer based water level prediction in Poyang Lake, China
Water level is an important indicator of lake hydrology characteristics, and its fluctuation
significantly affects lake ecosystems. In recent years, deep learning models have shown …
significantly affects lake ecosystems. In recent years, deep learning models have shown …
Annual and monthly dam inflow prediction using Bayesian networks
P Noorbeh, A Roozbahani… - Water Resources …, 2020 - Springer
Dam inflow prediction is important in terms of optimal water allocation and reduction of
potential risks of floods and droughts. It is necessary to select a suitable model to reduce …
potential risks of floods and droughts. It is necessary to select a suitable model to reduce …
Comparison between SARIMA and Holt–Winters models for forecasting monthly streamflow in the western region of Cuba
GR Alonso Brito, A Rivero Villaverde, A Lau Quan… - SN Applied …, 2021 - Springer
The present study aims to compare SARIMA and Holt–Winters model forecasts of mean
monthly flow at the V Aniversario basin, western Cuba. Model selection and model …
monthly flow at the V Aniversario basin, western Cuba. Model selection and model …
Advancing reservoir water level predictions: Evaluating conventional, ensemble and integrated swarm machine learning approaches
I Rehamnia, A Mahdavi-Meymand - Water Resources Management, 2024 - Springer
Accurate estimation of reservoir water level fluctuation (WLF) is crucial for effective dam
operation and environmental management. In this study, seven machine learning (ML) …
operation and environmental management. In this study, seven machine learning (ML) …
[HTML][HTML] Deep learning for Multi-horizon Water levelForecasting in KRS reservoir, India
In recent times, the densely populated Bengaluru metropolis in India has faced challenges
related to water scarcity, particularly relying on the Krishna Raja Sagara (KRS) dam. The …
related to water scarcity, particularly relying on the Krishna Raja Sagara (KRS) dam. The …
Performance comparison of techniques for water demand forecasting
P Vijai, PB Sivakumar - Procedia computer science, 2018 - Elsevier
There is an ever growing demand of water due to the factors like global warming,
urbanization and population growth. The situation demands to use more efficient planning …
urbanization and population growth. The situation demands to use more efficient planning …
A systematic review on machine learning algorithms used for forecasting lake‐water level fluctuations
SR Sannasi Chakravarthy… - Concurrency and …, 2022 - Wiley Online Library
Globally, the water‐level fluctuations in lakes are a dynamic and complex process. The
fluctuation is characterized by higher non‐linearity and stochasticity, making it quite hard to …
fluctuation is characterized by higher non‐linearity and stochasticity, making it quite hard to …
Data-driven approaches for meteorological time series prediction: a comparative study of the state-of-the-art computational intelligence techniques
With the proliferation of sensor generated weather data, the data-driven modeling for
prediction of meteorological time series has gained increasing research interest in current …
prediction of meteorological time series has gained increasing research interest in current …